Application Of Compressed Sensing In Limited Feedback Precoding

With multiple antennas at base station and User side,the technology of multi-input multi-output(MIMO)can break through the limitation of system bandwidth and transmitting power.so that the throughput of the system can be increased and the spectrum utilization of the system can be improved well.Orthogonal frequency division multiplexing(OFDM)technology is a kind of multiplexing modulation of multi carrier technology,the characteristic is that each sub carrier is orthogonal with each other,and the cyclic prefix is used as the guard interval,which can avoid the interference caused by the overlapping of different sub-carriers.OFDM not only can improve frequency selective fading,but also can effectively improve the system spectrum utilization.Therefore,combining MIMO with OFDM technology can not only improve system throughput,but also can reduce the bit error rate.In order to further improve the overall performance of the system,the send data stream can use pre-coding processing at transmitter.The prerequisite for pre-coding is that the sender obtains complete channel state information,but the feed backing of complete channel state information will occupy a large number of band resources of the feedback link.Therefore,how to use a small amount of feedback data could make almost the same effect with the complete channel state information,which is the hotspot in recent years.In this paper,compressed sensing technology is used in the system of limited feedback precoding,aiming to how to reduce the amount of feedback data and improve the reconstruction accuracy,the following work has been done.1.In order to reduce overhead of the feedback link,pre-coding algorithm of limited feedback based on compressed sensing is proposed,and the advantages of KL sparse is used to sparse the CSI which is estimated,the simulation results show that,without losing the characteristics of the channel information,the amount feedback of data is reduced more.2.Aiming at the defects of OMP algorithm,the improved OMP algorithm which is based on two selections and reconstruction of the weighted least squares method is proposed,then the traditional OMP and ROMP algorithm are simulated,and the simulation results verify the effectiveness of the improved algorithm.3.Put forward the application of Compressed Sensing to Massive MIMO system with limited feedback.And the simulation analysis of improved joint sparse algorithm is given.The simulation results show that the joint sparse can choose the observation matrix more appropriate,so that the overhead of feedback link will be reduced very well.